Obstacle avoidance using wall-following strategy for indoor mobile robots

Al-Mutib, Khalid; Faisal, Mohammed; Alsulaiman, Mansour; Abdessemed, Foudil; Hedjar, Ramdane; Bencherif, Mohamed

doi:10.1109/roma.2016.7847817

Cited by 13 publications

(18 citation statements)

References 12 publications

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“…Wall-following control law based on interval type-2 fuzzy logic was also proposed in [131,271,272] for path planning and obstacle avoidance while trying to improve noise resistance ability. Recently, Al-Mutib and Adessemed [273] tried to address the oscillation and data uncertainties problems and proposed a fuzzy logic wallfollowing technique based on type-2 fuzzy sets for obstacle avoidance for indoor mobile robots. The fuzzy controller proposed relied on the distance and orientation of the robot to the object as inputs to generate the needed wheel velocities to move the robot smoothly to its target while switching to the obstacle avoidance algorithm designed to avoid obstacles.…”

Section: Other Hybrid Methods That Include Flmentioning

confidence: 99%

“…Because hybrid methods are combination of multiple methods, they possess comparatively higher merits by taking advantage of the strengths of the integrated methods while minimizing the drawbacks of these methods. For instance, integration of appropriate methods can help improve noise resistance ability and deal better with oscillation and data uncertainties and controlling local minima problem associated with APF [36,131,171,272,273]. Though hybrid methods seem to possess the strengths of the methods integrated while reducing their drawbacks, there are still challenges using them.…”

Section: Strengths and Challenges Of Hybrid Path Planning Methodsmentioning

confidence: 99%

“…The drawbacks of each approach in the combination is reduced. Example: Improves noise resistance ability, deal better with oscillation and data uncertainties [131,[271][272][273] and controlling local minima problem associated with APF [36] Noise from sensor and cameras and the hardware constraints including the limitation of motor speed, imbalance mass of the robot, power supply to the motors and many others affects the practical performance of these approaches.…”

Section: Simulation and Real Experimentsmentioning

confidence: 99%

See 2 more Smart Citations

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.

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Section: Other Hybrid Methods That Include Flmentioning

confidence: 99%

Section: Strengths and Challenges Of Hybrid Path Planning Methodsmentioning

confidence: 99%

Section: Simulation and Real Experimentsmentioning

confidence: 99%

See 1 more Smart Citation

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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“…Por ejemplo en (Van Turennout presentan ruidos provenientes de otras fuentes de señales no deseadas al detectar obstáculos. En consecuencia, el detectar dichos obstáculos y posicionar correctamente el robot frente a una pared se vuelve un problema lleno de incertidumbres como se describe en (Al-Mutib et al, 2016). Por esta razón varios autores han propuesto diferentes enfoques inteligentes con el objetivo de disminuir este problema.…”

Section: Introductionunclassified

Controlador PD-Difuso para Seguimiento de Pared de un Robot Móvil: Validación Experimental

et al. 2019

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Este artículo presenta un controlador Fuzzy-PD para resolver el problema de seguimiento de pared a través de un robot móvil. El desempeño del controlador propuesto es comparado con un controlador clásico PD a través del análisis del índice de la integral del error cuadrático (ISE) y el índice de variación total de la acción de control (TV). Para el diseño del controlador Fuzzy-PD, se consideró la distancia que existe entre el robot móvil y la pared la cual es medida a través de un sensor ultrasónico que tiene el robot. En este trabajo se realizaron dos pruebas con el objetivo de mostrar la efectividad que posee cada controlador; un cambio de referencia de la distancia de seguimiento y el seguimiento de una pared desconocida. Los controladores fueron sintonizados a través del algoritmo de optimización por enjambre de partículas (PSO) e implementados en la plataforma DaNI 2.0 mediante el uso del software LabView Robotics.

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“…The mobile robots for avoiding obstacles were addressed in [7][8][9][10][11]. A mobile robot was operated in the warehouse for transferring the objects [7].…”

Section: Introductionmentioning

confidence: 99%

Implementation of Fuzzy Logic Controller for Wall Following and Obstacle Avoiding Robot

Soetedjo

Ashari

Septian

2019

JAIS

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This paper presents the development of wall following and obstacle avoiding robot using a Fuzzy Logic Controller. The ultrasonic sensors are employed to measure the distances between robot and the wall, and between the robot and the obstacle. A low cost Raspberry Pi camera is employed to measure the left/right distance between the robot and the obstacle. The Fuzzy Logic Controller is employed to steer the mobile robot to follow the wall and avoid the obstacle according to the multi sensor inputs. The outputs of Fuzzy Logic Controller are the speeds of left motor and right motor. The experimental results show that the developed mobile robot could be controlled properly to follow the different wall positions and avoid the different obstacle positions with the high successful rate of 83.33%.

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Obstacle avoidance using wall-following strategy for indoor mobile robots

Cited by 13 publications

References 12 publications

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Controlador PD-Difuso para Seguimiento de Pared de un Robot Móvil: Validación Experimental

Implementation of Fuzzy Logic Controller for Wall Following and Obstacle Avoiding Robot

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